Quantitative analysis of F‐actin redistribution in astrocytoma cells treated with candidate pharmaceuticals

Abstract

Actin fibers (F-actin) control the shape and internal organization of cells, and generate force. It has been long appreciated that these functions are tightly coupled, and in some cases drive cell behavior and cell fate. The distribution and dynamics of F-actin is different in cancer versus normal cells and in response to small molecules, including actin-targeting natural products and anticancer drugs. Therefore, quantifying actin structural changes from high resolution fluorescence micrographs is necessary for further understanding actin cytoskeleton dynamics and phenotypic consequences of drug interactions on cells. We applied an artificial neural network algorithm, which used image intensity and anisotropy measurements, to quantitatively classify F-actin subcellular features into actin along the edges of cells, actin at the protrusions of cells, internal fibers and punctate signals. The algorithm measured significant increase in F-actin at cell edges with concomitant decrease in internal punctate actin in astrocytoma cells lacking functional neurofibromin and p53 when treated with three structurally-distinct anticancer small molecules: OSW1, Schweinfurthin A (SA) and a synthetic marine compound 23′-dehydroxycephalostatin 1. Distinctly different changes were measured in cells treated with the actin inhibitor cytochalasin B. These measurements support published reports that SA acts on F-actin in NF1−/− neurofibromin deficient cancer cells through changes in Rho signaling. Quantitative pattern analysis of cells has wide applications for understanding mechanisms of small molecules, because many anticancer drugs directly or indirectly target cytoskeletal proteins. Furthermore, quantitative information about the actin cytoskeleton may make it possible to further understand cell fate decisions using mathematically testable models. Published 2014 Wiley Periodicals Inc.†

Schweinfurthins: Lipid Modulators with Promising Anticancer Activity

“…However, schweinfurthin‐insensitive cells, such as the lung cancer cell line A549 and primary astrocytes, do not display morphological changes (Turbyville et al, ). In , Lockett et al developed a computational program to quantify and identify types of actins based on the intensity and anisotropy of each pixel in a high‐resolution fluorescent micrograph. With this algorithm, they determined that treatment with schweinfurthin A increases levels of peripheral F‐actin bundles and decreases internal punctate actin (Lockett et al, ).…”

“…In , Lockett et al developed a computational program to quantify and identify types of actins based on the intensity and anisotropy of each pixel in a high‐resolution fluorescent micrograph. With this algorithm, they determined that treatment with schweinfurthin A increases levels of peripheral F‐actin bundles and decreases internal punctate actin (Lockett et al, ). Intriguingly, cells treated with schweinfurthins display a similar decrease in stress fibers and increase in marginal cortical actin as cells treated with the Rho inhibitor C3 transferase and the Rock inhibitor Y‐27632 (Cui et al, ; Turbyville et al, ).…”

A spatiotemporal characterization method for the dynamic cytoskeleton

“…Biomedically, D f has also been used as a numerical measure of retinal vascular branching [Liew et al, ; Cheung et al, ], neuronal branching and extension [Milošević et al, ; Shigetomi et al, ] and mammary epithelial ducting networks [Fuseler et al, ]. Other investigators have also used it to measure cytoskeleton disruptions resulting from drug treatments [Lockett et al, ] or external forces[Qian et al, ],but is fractal analysis sufficiently sensitive to detect subtle physiological changes? Another approach for cytoskeletal analyses, the coherence method, was unable to differentiate the cytoskeletal arrangement in control cells and cells infected with a virus, but showed significant changes only when cells were treated with anti‐cytoskeletal drugs such as Cytochalasin [Weichsel et al, ].…”

A spatiotemporal characterization method for the dynamic cytoskeleton

“…Biomedically, D f has also been used as a numerical measure of retinal vascular branching [Liew et al, 2008;Cheung et al, 2014], neuronal branching and extension [Milo sević et al, 2007;Shigetomi et al, 2013] and mammary epithelial ducting networks [Fuseler et al, 2014]. Other investigators have also used it to measure cytoskeleton disruptions resulting from drug treatments [Lockett et al, 2014] or external forces [Qian et al, 2012],but is fractal analysis sufficiently sensitive to detect subtle physiological changes? Another approach for cytoskeletal analyses, the coherence method, was unable to differentiate the cytoskeletal arrangement in control cells and cells infected with a virus, but showed significant changes only when cells were treated with anti-cytoskeletal drugs such as Cytochalasin [Weichsel et al, 2010].…”

“…Unlike previous work using D f as a measurement of cytoskeleton complexity [Lockett et al, 2014], our study is not limited to differentiating cytoskeletal arrangements of cells exposed to agents capable of major cytoskeletal disruption. Rather, this study focuses on transgenically-modified human dermal fibroblasts (HDF, LifeAct.mCherry) cultured on (1) polyacrylamide (PA) gels of different stiffness and (2) PA gels coated with Collagen I (Col) or Fibronectin (Fn) to confirm that fractal analysis is sensitive enough to detect minor differences that are more physiologically relevant.…”